The use of digital attributes stored in the cookies of personal devices has proliferated and there has come to exist an abundance of data in the form of individual information from a user. Such datasets are rich in information and have consequently attracted much attention in disciplines relating to data analytics. Digital datasets have been mined and analyzed for applications such as tracking the websites a user frequents including those used for shopping or general interests. Typically, a digital dataset can be regarded as being indicative of the activity preference of the user.
Generally, in analyzing the digital dataset, physical attributes stored by sensor device cookies of a user's personal device such as a smart phone, have not yet been grouped with the digital activity of the user. This combination of information of physical and digital information can lead to pinpointing one or more interests/habits of an individual user. With sensors becoming ubiquitous, ranging from smart phone sensors to sensors embedded in the digital infrastructure of a user, people are creating personal traces of both digital activity as well as physical location activity. Combined, these activity and location traces indicate future activity of a user. Challenges continue with respect to completely sharing and combining both the digital and physical information gleaned from a user.